from flask import Flask, jsonify
import cx_Oracle
app = Flask(__name__)
def get_database_connection():
    dsn = cx_Oracle.makedsn('host', 'port', service_name='service_name')
    connection = cx_Oracle.connect(user='username', password='password', dsn=dsn)
    return connection
@app.route('/api/dashboard/menu', methods=['GET'])
def get_menu():
    connection = get_database_connection()
    cursor = connection.cursor()
    query = "SELECT name FROM menu_items WHERE type = :type"
    cursor.execute(query, {'type': 'main_menu'})
    menu_items = []
    for row in cursor.fetchall():
        menu_items.append({'name': row[0]})
    cursor.close()
    connection.close()
    response_data = {
        "data": [
            {
                "data": menu_items,
                "type": "menu",
                "count": len(menu_items)
            }
        ],
        "name": "主菜单导航",
        "type": "menu",
        "index": 0
    }
    return jsonify(response_data)
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, request, jsonify
from functools import wraps
import re
app = Flask(__name__)
class ValidationError(Exception):
    pass
def validate_request(f):
    @wraps(f)
    def decorated_function(*args, **kwargs):
        if request.method == 'GET':
            return validate_get_request()
        elif request.method == 'POST':
            return validate_post_request()
        elif request.method == 'DELETE':
            return validate_delete_request()
        return f(*args, **kwargs)
    return decorated_function
def validate_get_request():
    required_params = ['id']
    errors = []
    for param in required_params:
        if param not in request.args:
            errors.append(f'Missing required parameter: {param}')
    if errors:
        raise ValidationError(errors)
    return None
def validate_post_request():
    required_fields = ['name', 'email', 'age']
    errors = []
    for field in required_fields:
        if field not in request.json:
            errors.append(f'Missing required field: {field}')
        elif field == 'email' and not is_valid_email(request.json[field]):
            errors.append(f'Invalid email format: {request.json[field]}')
        elif field == 'age' and not isinstance(request.json[field], int):
            errors.append(f'Age must be an integer: {request.json[field]}')
    if errors:
        raise ValidationError(errors)
    return None
def validate_delete_request():
    required_params = ['id']
    errors = []
    for param in required_params:
        if param not in request.args:
            errors.append(f'Missing required parameter: {param}')
    if errors:
        raise ValidationError(errors)
    return None
def is_valid_email(email):
    regex = r'^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$'
    return re.match(regex, email) is not None
@app.errorhandler(ValidationError)
def handle_validation_error(error):
    response = jsonify({'errors': error.args[0]})
    response.status_code = 400
    return response
@app.route('/data', methods=['GET', 'POST', 'DELETE'])
@validate_request
def handle_data():
    if request.method == 'GET':
        id = request.args.get('id')
        return jsonify({'message': f'Getting data for id: {id}'})
    elif request.method == 'POST':
        name = request.json['name']
        email = request.json['email']
        age = request.json['age']
        return jsonify({'message': f'Created data for {name}, email: {email}, age: {a
ge}'})
    elif request.method == 'DELETE':
        id = request.args.get('id')
        return jsonify({'message': f'Deleted data for id: {id}'})
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify
import cx_Oracle
app = Flask(__name__)
def get_db_connection():
    dsn = cx_Oracle.makedsn("hostname", "port", sid="sid")
    connection = cx_Oracle.connect(user="username", password="password", dsn=dsn)
    return connection
@app.route('/api/realtime_visualization/home', methods=['GET'])
def realtime_visualization_home():
    connection = get_db_connection()
    cursor = connection.cursor()
    # 示例 SQL 查询，查询
    cursor.execute("""
        SELECT 
            TO_CHAR(date_column, 'MM') AS month,
            SUM(visit_count) AS visit_count
        FROM 
            visits
        WHERE 
            date_column >= TRUNC(SYSDATE, 'MM') - INTERVAL '5' MONTH AND date_column 
< TRUNC(SYSDATE, 'MM') + INTERVAL '1' MONTH
        GROUP BY 
            TO_CHAR(date_column, 'MM')
        ORDER BY 
            TO_CHAR(date_column, 'MM')
    """)
    results = cursor.fetchall()
    months = ["一月访问量", "二月访问量", "三月访问量", "四月访问量", "五月访问量", "
六月访问量"]
    visit_counts = [0] * len(months)
    for row in results:
        month_index = int(row[0]) - 1
        visit_counts[month_index] = row[1]
    cursor.close()
    connection.close()
    response_data = {
        "data": [
            {
                "data": [
                    {
                        "xAxis": months,
                        "yAxis": visit_counts,
                        "legend": ["实时增长", "历史比较"],
                    }
                ],
                "type": "echartLine",
                "count": 1,
                "legend": 2,
                "xcount": 1,
                "ycount": 1,
            }
        ],
        "name": "实时数据图表",
        "type": "echart",
        "index": 1,
    }
    return jsonify(response_data)
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, request, render_template
import random
import time
import threading
import json
app = Flask(__name__)
data_store = []
data_lock = threading.Lock()
def generate_random_data():
    while True:
        with data_lock:
            random_data = {
                "timestamp": time.time(),
                "value": random.uniform(0, 100)
            }
            data_store.append(random_data)
            if len(data_store) > 100:  # Limit data store to the last 100 entries
                data_store.pop(0)
        time.sleep(1)
@app.route('/api/data', methods=['GET'])
def get_data():
    with data_lock:
        return jsonify(data_store)
@app.route('/api/last', methods=['GET'])
def get_last_entry():
    with data_lock:
        if data_store:
            return jsonify(data_store[-1])
        else:
            return jsonify({"error": "No data available"}), 404
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/api/clear', methods=['POST'])
def clear_data():
    with data_lock:
        data_store.clear()
    return jsonify({"message": "Data cleared successfully"})
def run_flask():
    app.run(debug=True, port=5000)
if __name__ == '__main__':
    threading.Thread(target=generate_random_data, daemon=True).start()
    run_flask()
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-time Data Visualization</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>Real-time Data Visualization</h1>
    <canvas id="dataChart" width="400" height="200"></canvas>
    <button id="clearData">Clear Data</button>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        const chartData = {
            labels: [],
            datasets: [{
                label: 'Random Data',
                borderColor: 'rgba(75, 192, 192, 1)',
                borderWidth: 1,
                fill: false,
                data: []
            }]
        };
        const config = {
            type: 'line',
            data: chartData,
            options: {
                scales: {
                    x: {
                        type: 'linear',
                        position: 'bottom'
                    }
                }
            }
        };
        const dataChart = new Chart(ctx, config);
        async function fetchData() {
            const response = await fetch('/api/data');
            const data = await response.json();
            return data;
        }
        async function updateChart() {
            const data = await fetchData();
            dataChart.data.labels = data.map(entry => new Date(entry.timestamp * 1000
).toLocaleTimeString());
            dataChart.data.datasets[0].data = data.map(entry => entry.value);
            dataChart.update();
        }
        document.getElementById('clearData').addEventListener('click', async () => {
            await fetch('/api/clear', { method: 'POST' });
            dataChart.data.labels = [];
            dataChart.data.datasets[0].data = [];
            dataChart.update();
        });
        setInterval(updateChart, 1000);
    </script>
</body>
</html>
from flask import Flask, request, jsonify
import cx_Oracle
app = Flask(__name__)
db_connection = cx_Oracle.connect('username', 'password', 'host:port/service_name')
cursor = db_connection.cursor()
@app.route('/user_behavior', methods=['GET', 'POST', 'PUT', 'DELETE'])
def user_behavior():
    if request.method == 'GET':
        cursor.execute("SELECT * FROM user_behavior")
        rows = cursor.fetchall()
        return jsonify([dict(row) for row in rows])
    elif request.method == 'POST':
        data = request.json
        insert_query = "INSERT INTO user_behavior (user_id, behavior_type, timestamp)
 VALUES (:1, :2, :3)"
        cursor.execute(insert_query, (data['user_id'], data['behavior_type'], data['t
imestamp']))
        db_connection.commit()
        return jsonify({"message": "Behavior data added"}), 201
    elif request.method == 'PUT':
        data = request.json
        update_query = "UPDATE user_behavior SET behavior_type = :1, timestamp = :2 W
HERE id = :3"
        cursor.execute(update_query, (data['behavior_type'], data['timestamp'], data[
'id']))
        db_connection.commit()
        return jsonify({"message": "Behavior data updated"})
    elif request.method == 'DELETE':
        behavior_id = request.args.get('id')
        delete_query = "DELETE FROM user_behavior WHERE id = :1"
        cursor.execute(delete_query, (behavior_id,))
        db_connection.commit()
        return jsonify({"message": "Behavior data deleted"})
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify
import os
import logging
class Config:
    DEBUG = True
    TESTING = False
    SECRET_KEY = os.environ.get('SECRET_KEY', 'default-secret-key')
    DATABASE_URI = os.environ.get('DATABASE_URI', 'sqlite:///default.db')
    LOGGING_LEVEL = os.environ.get('LOGGING_LEVEL', logging.INFO)
    ALLOWED_HOSTS = os.environ.get('ALLOWED_HOSTS', '*').split(',')
class DevelopmentConfig(Config):
    DEBUG = True
    DATABASE_URI = os.environ.get('DEV_DATABASE_URI', 'sqlite:///dev.db')
class TestingConfig(Config):
    TESTING = True
    DATABASE_URI = os.environ.get('TEST_DATABASE_URI', 'sqlite:///test.db')
class ProductionConfig(Config):
    DEBUG = False
    DATABASE_URI = os.environ.get('PROD_DATABASE_URI', 'sqlite:///prod.db')
configurations = {
    'development': DevelopmentConfig,
    'testing': TestingConfig,
    'production': ProductionConfig
}
def create_app(config_name):
    app = Flask(__name__)
    app.config.from_object(configurations[config_name])
    logging.basicConfig(level=app.config['LOGGING_LEVEL'])
    logger = logging.getLogger(__name__)
    @app.route('/config')
    def get_config():
        return jsonify({
            'DEBUG': app.config['DEBUG'],
            'DATABASE_URI': app.config['DATABASE_URI'],
            'ALLOWED_HOSTS': app.config['ALLOWED_HOSTS']
        })
    return app
from flask import Flask, jsonify, render_template
import random
import time
import threading
app = Flask(__name__)
data_store = []
def generate_random_data():
    while True:
        current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
        random_value = random.uniform(0, 100)
        data_store.append({'time': current_time, 'value': random_value})
        time.sleep(1)
@app.route('/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/')
def index():
    return render_template('index.html')
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.start()
    app.run(debug=True)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>实时数据分析可视化</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>实时数据分析可视化</h1>
    <canvas id="myChart" width="400" height="200"></canvas>
    <script>
        const ctx = document.getElementById('myChart').getContext('2d');
        let myChart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: '随机数据',
                    data: [],
                    borderColor: 'rgba(75, 192, 192, 1)',
                    borderWidth: 1
                }]
            },
            options: {
                scales: {
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        function fetchData() {
            fetch('/data')
            .then(response => response.json())
            .then(data => {
                myChart.data.labels = data.map(entry => entry.time);
                myChart.data.datasets[0].data = data.map(entry => entry.value);
                myChart.update();
            });
        }
        setInterval(fetchData, 2000);
    </script>
</body>
</html>
from flask import Flask, request, jsonify
import cx_Oracle
app = Flask(__name__)
# Database connection
def get_db_connection():
    dsn = cx_Oracle.makedsn("hostname", "port", service_name="service_name")
    connection = cx_Oracle.connect(user="username", password="password", dsn=dsn)
    return connection
@app.route('/history', methods=['GET'])
def get_history_data():
    connection = get_db_connection()
    cursor = connection.cursor()
    query = "SELECT * FROM history_data"
    cursor.execute(query)
    rows = cursor.fetchall()
    cursor.close()
    connection.close()
    return jsonify(rows)
@app.route('/history/<int:data_id>', methods=['GET'])
def get_history_record(data_id):
    connection = get_db_connection()
    cursor = connection.cursor()
    query = "SELECT * FROM history_data WHERE data_id = :data_id"
    cursor.execute(query, data_id=data_id)
    row = cursor.fetchone()
    cursor.close()
    connection.close()
    return jsonify(row)
@app.route('/history', methods=['POST'])
def add_history_record():
    new_record = request.json
    connection = get_db_connection()
    cursor = connection.cursor()
    query = "INSERT INTO history_data (data_field_1, data_field_2, data_field_3) VALU
ES (:field1, :field2, :field3)"
    cursor.execute(query, field1=new_record['field1'], field2=new_record['field2'], f
ield3=new_record['field3'])
    connection.commit()
    cursor.close()
    connection.close()
    return jsonify(new_record), 201
@app.route('/history/<int:data_id>', methods=['PUT'])
def update_history_record(data_id):
    update_record = request.json
    connection = get_db_connection()
    cursor = connection.cursor()
    query = "UPDATE history_data SET data_field_1 = :field1, data_field_2 = :field2, 
data_field_3 = :field3 WHERE data_id = :data_id"
    cursor.execute(query, field1=update_record['field1'], field2=update_record['field
2'], field3=update_record['field3'], data_id=data_id)
    connection.commit()
    cursor.close()
    connection.close()
    return jsonify(update_record)
@app.route('/history/<int:data_id>', methods=['DELETE'])
def delete_history_record(data_id):
    connection = get_db_connection()
    cursor = connection.cursor()
    query = "DELETE FROM history_data WHERE data_id = :data_id"
    cursor.execute(query, data_id=data_id)
    connection.commit()
    cursor.close()
    connection.close()
    return jsonify({'message': 'Record deleted successfully'}), 204
if __name__ == "__main__":
    app.run(debug=True)
from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy.exc import SQLAlchemyError
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'oracle://username:password@hostname:port/dbname'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
class Configuration(db.Model):
    __tablename__ = 'configurations'
    id = db.Column(db.Integer, primary_key=True)
    key = db.Column(db.String(100), nullable=False, unique=True)
    value = db.Column(db.Text, nullable=False)
db.create_all()
@app.route('/configurations', methods=['GET'])
def get_configurations():
    try:
        configurations = Configuration.query.all()
        return jsonify([{'id': config.id, 'key': config.key, 'value': config.value} f
or config in configurations])
    except SQLAlchemyError as e:
        return jsonify({'error': str(e)}), 500
@app.route('/configuration/<int:id>', methods=['GET'])
def get_configuration(id):
    try:
        configuration = Configuration.query.get(id)
        if configuration:
            return jsonify({'id': configuration.id, 'key': configuration.key, 'value'
: configuration.value})
        else:
            return jsonify({'error': 'Configuration not found'}), 404
    except SQLAlchemyError as e:
        return jsonify({'error': str(e)}), 500
@app.route('/configurations', methods=['POST'])
def create_configuration():
    try:
        data = request.get_json()
        new_config = Configuration(key=data['key'], value=data['value'])
        db.session.add(new_config)
        db.session.commit()
        return jsonify({'message': 'Configuration created', 'id': new_config.id}), 201
    except KeyError:
        return jsonify({'error': 'Key and Value are required'}), 400
    except SQLAlchemyError as e:
        return jsonify({'error': str(e)}), 500
@app.route('/configuration/<int:id>', methods=['PUT'])
def update_configuration(id):
    try:
        data = request.get_json()
        configuration = Configuration.query.get(id)
        if not configuration:
            return jsonify({'error': 'Configuration not found'}), 404
        if 'key' in data:
            configuration.key = data['key']
        if 'value' in data:
            configuration.value = data['value']
        db.session.commit()
        return jsonify({'message': 'Configuration updated'})
    except KeyError:
        return jsonify({'error': 'Invalid data format'}), 400
    except SQLAlchemyError as e:
        return jsonify({'error': str(e)}), 500
@app.route('/configuration/<int:id>', methods=['DELETE'])
def delete_configuration(id):
    try:
        configuration = Configuration.query.get(id)
        if not configuration:
            return jsonify({'error': 'Configuration not found'}), 404
        db.session.delete(configuration)
        db.session.commit()
        return jsonify({'message': 'Configuration deleted'})
    except SQLAlchemyError as e:
        return jsonify({'error': str(e)}), 500
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify
import cx_Oracle
app = Flask(__name__)
def get_oracle_connection():
    dsn = cx_Oracle.makedsn("hostname", 1521, service_name="service_name")
    connection = cx_Oracle.connect(user="username", password="password", dsn=dsn)
    return connection
@app.route('/api/realtime_overview', methods=['GET'])
def realtime_overview():
    response = {
        "data": [
            {
                "data": [
                    {
                        "xAxis": ["一月发电量", "二月发电量", "三月发电量", "四月发电
量", "五月发电量", "六月发电量"],
                        "yAxis": [90, 70, 80, 65, 75, 85],
                        "legend": ["日统计", "周统计", "月统计"]
                    }
                ],
                "type": "echartLine",
                "count": 1,
                "legend": 3,
                "xcount": 6,
                "ycount": 8
            },
            {
                "data": {
                    "data": get_environment_testing_data(),
                    "header": [
                        {"th": "检测日期", "value": "test_date"},
                        {"th": "样本编号", "value": "sample_id"},
                        {"th": "检测项目", "value": "test_item"},
                        {"th": "检测仪器编号", "value": "instrument_id"},
                        {"th": "检测结果", "value": "test_result"}
                    ]
                },
                "type": "table",
                "count": 1,
                "tdcount": 4,
                "thcount": 4
            }
        ],
        "name": "数据统计概览",
        "type": "statistics",
        "index": 3
    }
    return jsonify(response)
def get_environment_testing_data():
    connection = get_oracle_connection()
    cursor = connection.cursor()
    cursor.execute("SELECT sample_id, test_date, test_item, instrument_id, test_resul
t FROM environment_testing ORDER BY test_date DESC FETCH FIRST 4 ROWS ONLY")
    results = cursor.fetchall()
    cursor.close()
    connection.close()
    data = []
    for row in results:
        data.append({
            "sample_id": row[0],
            "test_date": row[1].strftime('%Y-%m-%d'),
            "test_item": row[2],
            "instrument_id": row[3],
            "test_result": row[4],
            "test_report_image": "http://example.com/image{}.jpg".format(row[0][-1]), 
            "monitoring_location": "地点{}".format(row[0][-1])
        })
    return data
if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)
from flask import Flask, jsonify, render_template
import random
import time
import threading
app = Flask(__name__)
data_store = {
    "temperature": [],
    "humidity": [],
    "pressure": []
}
def generate_random_data():
    while True:
        temp = round(random.uniform(15.0, 30.0), 2)
        humidity = round(random.uniform(30.0, 70.0), 2)
        pressure = round(random.uniform(950.0, 1050.0), 2)
        data_store["temperature"].append(temp)
        data_store["humidity"].append(humidity)
        data_store["pressure"].append(pressure)
        if len(data_store["temperature"]) > 100:
            data_store["temperature"].pop(0)
            data_store["humidity"].pop(0)
            data_store["pressure"].pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/api/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    app.run(host='0.0.0.0', port=5000)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-time Data Visualization</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>Real-time Data Visualization</h1>
    <canvas id="temperatureChart"></canvas>
    <canvas id="humidityChart"></canvas>
    <canvas id="pressureChart"></canvas>
    <script>
        const tempCtx = document.getElementById('temperatureChart').getContext('2d');
        const humidityCtx = document.getElementById('humidityChart').getContext('2d');
        const pressureCtx = document.getElementById('pressureChart').getContext('2d');
        const temperatureChart = new Chart(tempCtx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: 'Temperature (°C)',
                    data: [],
                    borderColor: 'rgba(255, 99, 132, 1)',
                    borderWidth: 1
                }]
            },
            options: {
                scales: {
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        const humidityChart = new Chart(humidityCtx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: 'Humidity (%)',
                    data: [],
                    borderColor: 'rgba(54, 162, 235, 1)',
                    borderWidth: 1
                }]
            },
            options: {
                scales: {
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        const pressureChart = new Chart(pressureCtx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: 'Pressure (hPa)',
                    data: [],
                    borderColor: 'rgba(75, 192, 192, 1)',
                    borderWidth: 1
                }]
            },
            options: {
                scales: {
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        function fetchData() {
            fetch('/api/data')
                .then(response => response.json())
                .then(data => {
                    const currentTime = new Date().toLocaleTimeString();
                    if (temperatureChart.data.labels.length >= 100) {
                        temperatureChart.data.labels.shift();
                        humidityChart.data.labels.shift();
                        pressureChart.data.labels.shift();
                    }
                    temperatureChart.data.labels.push(currentTime);
                    humidityChart.data.labels.push(currentTime);
                    pressureChart.data.labels.push(currentTime);
                    temperatureChart.data.datasets[0].data.push(data.temperature[data
.temperature.length - 1]);
                    humidityChart.data.datasets[0].data.push(data.humidity[data.humid
ity.length - 1]);
                    pressureChart.data.datasets[0].data.push(data.pressure[data.press
ure.length - 1]);
                    temperatureChart.update();
                    humidityChart.update();
                    pressureChart.update();
                });
        }
        setInterval(fetchData, 1000);
    </script>
</body>
</html>
from flask import Flask, request, jsonify
import cx_Oracle
app = Flask(__name__)
dsn_tns = cx_Oracle.makedsn('host', 'port', service_name='service_name')
connection = cx_Oracle.connect(user='user', password='password', dsn=dsn_tns)
@app.route('/monitor', methods=['GET'])
def get_monitor_data():
    cursor = connection.cursor()
    cursor.execute("SELECT * FROM real_time_monitoring")
    result = cursor.fetchall()
    cursor.close()
    return jsonify(result), 200
@app.route('/monitor', methods=['POST'])
def add_monitor_data():
    data = request.json
    cursor = connection.cursor()
    cursor.execute(
        "INSERT INTO real_time_monitoring (id, metric, value, timestamp) VALUES (:id,
 :metric, :value, :timestamp)",
        id=data['id'], metric=data['metric'], value=data['value'], timestamp=data['ti
mestamp']
    )
    connection.commit()
    cursor.close()
    return jsonify({"message": "Data added successfully"}), 201
@app.route('/monitor/<int:id>', methods=['PUT'])
def update_monitor_data(id):
    data = request.json
    cursor = connection.cursor()
    cursor.execute(
        "UPDATE real_time_monitoring SET metric = :metric, value = :value, timestamp 
= :timestamp WHERE id = :id",
        metric=data['metric'], value=data['value'], timestamp=data['timestamp'], id=id
    )
    connection.commit()
    cursor.close()
    return jsonify({"message": "Data updated successfully"}), 200
@app.route('/monitor/<int:id>', methods=['DELETE'])
def delete_monitor_data(id):
    cursor = connection.cursor()
    cursor.execute("DELETE FROM real_time_monitoring WHERE id = :id", id=id)
    connection.commit()
    cursor.close()
    return jsonify({"message": "Data deleted successfully"}), 204
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, request
import pika
import json
import logging
app = Flask(__name__)
logging.basicConfig(level=logging.INFO)
class MessageQueue:
    def __init__(self, host='localhost'):
        self.connection = None
        self.channel = None
        self.host = host
        self.queue_name = 'data_queue'
    def connect(self):
        try:
            self.connection = pika.BlockingConnection(pika.ConnectionParameters(host=
self.host))
            self.channel = self.connection.channel()
            self.channel.queue_declare(queue=self.queue_name)
            logging.info("Connected to message queue")
        except Exception as e:
            logging.error(f"Error connecting to message queue: {e}")
            raise
    def publish(self, message):
        try:
            if not self.channel:
                raise Exception("Channel not initialized.")
            self.channel.basic_publish(exchange='', routing_key=self.queue_name, body
=json.dumps(message))
            logging.info(f"Published message: {message}")
        except Exception as e:
            logging.error(f"Error publishing message: {e}")
            raise
    def consume(self, callback):
        try:
            if not self.channel:
                raise Exception("Channel not initialized.")
            self.channel.basic_consume(queue=self.queue_name, on_message_callback=cal
lback, auto_ack=True)
            logging.info("Starting to consume messages")
            self.channel.start_consuming()
        except Exception as e:
            logging.error(f"Error consuming message: {e}")
            raise
    def close(self):
        try:
            if self.connection:
                self.connection.close()
                logging.info("Connection closed")
        except Exception as e:
            logging.error(f"Error closing connection: {e}")
            raise
mq = MessageQueue()
@app.route('/publish', methods=['POST'])
def publish_message():
    data = request.get_json()
    if not data:
        return jsonify({"error": "Invalid data"}), 400
    try:
        mq.publish(data)
        return jsonify({"status": "Message published"}), 200
    except Exception as e:
        return jsonify({"error": str(e)}), 500
@app.route('/consume', methods=['GET'])
def consume_messages():
    try:
        def callback(ch, method, properties, body):
            logging.info(f"Received message: {body}")
        mq.consume(callback)
        return jsonify({"status": "Started consuming"}), 200
    except Exception as e:
        return jsonify({"error": str(e)}), 500
if __name__ == '__main__':
    try:
        mq.connect()
        app.run(debug=True)
    except Exception as e:
        logging.error(f"Error starting the application: {e}")
from flask import Flask, jsonify
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'oracle://username:password@host:port/dbname'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
class SystemPerformanceStatistics(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    cpu_usage_percentage = db.Column(db.Float)
    memory_usage_gb = db.Column(db.Float)
    network_latency_ms = db.Column(db.Float)
    active_users_count = db.Column(db.Integer)
    total_requests_count = db.Column(db.Integer)
    error_requests_count = db.Column(db.Integer)
    api_call_count = db.Column(db.Integer)
    data_loss_records = db.Column(db.Integer)
    successful_logins_count = db.Column(db.Integer)
@app.route('/api/realtime-dashboard', methods=['GET'])
def realtime_dashboard():
    statistics = SystemPerformanceStatistics.query.first()
    if not statistics:
        return jsonify({"error": "No data found"}), 404
    performance_data = {
        "name": "系统性能指标",
        "type": "statistics",
        "index": 5,
        "data": [
            {
                "data": [
                    {"name": "CPU使用率", "unit": "百分比", "value": statistics.cpu_u
sage_percentage},
                    {"name": "内存使用量", "unit": "GB", "value": statistics.memory_u
sage_gb},
                    {"name": "网络延迟", "unit": "毫秒", "value": statistics.network_
latency_ms}
                ],
                "type": "censusunit",
                "count": 3
            },
            {
                "data": [
                    {"name": "活跃用户数", "value": statistics.active_users_count},
                    {"name": "系统请求总数", "value": statistics.total_requests_count},
                    {"name": "错误请求数", "value": statistics.error_requests_count},
                    {"name": "API调用次数", "value": statistics.api_call_count},
                    {"name": "数据丢失记录", "value": statistics.data_loss_records},
                    {"name": "成功登录用户数", "value": statistics.successful_logins_
count}
                ],
                "type": "census",
                "count": 6
            }
        ]
    }
    return jsonify({"data": [performance_data]})
if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)
from flask import Flask, jsonify, request
import random
import time
import threading
app = Flask(__name__)
data_store = []
data_lock = threading.Lock()
def generate_random_data():
    while True:
        time.sleep(1)
        with data_lock:
            data_point = {
                'temperature': random.uniform(20.0, 30.0),
                'humidity': random.uniform(30.0, 70.0),
                'timestamp': time.time()
            }
            data_store.append(data_point)
@app.route('/api/data', methods=['GET'])
def get_data():
    with data_lock:
        return jsonify(data_store[-10:])
@app.route('/api/data/clear', methods=['DELETE'])
def clear_data():
    with data_lock:
        data_store.clear()
    return jsonify({'message': 'Data cleared successfully'})
@app.route('/api/data/latest', methods=['GET'])
def get_latest_data():
    with data_lock:
        if data_store:
            return jsonify(data_store[-1])
        else:
            return jsonify({'message': 'No data available'})
@app.route('/api/data/range', methods=['GET'])
def get_data_range():
    start_time = request.args.get('start')
    end_time = request.args.get('end')
    start_time = float(start_time) if start_time else 0
    end_time = float(end_time) if end_time else time.time()
    with data_lock:
        filtered_data = [dp for dp in data_store if start_time <= dp['timestamp'] <= 
end_time]
        return jsonify(filtered_data)
if __name__ == '__main__':
    data_generator_thread = threading.Thread(target=generate_random_data)
    data_generator_thread.daemon = True
    data_generator_thread.start()
    app.run(port=5000)
from flask import Flask, request, jsonify
import cx_Oracle
app = Flask(__name__)
dsn = cx_Oracle.makedsn("hostname", "port", service_name="service_name")
connection = cx_Oracle.connect(user="username", password="password", dsn=dsn)
@app.route('/data_overview', methods=['GET'])
def get_data_overview():
    with connection.cursor() as cursor:
        cursor.execute("SELECT * FROM data_overview")
        rows = cursor.fetchall()
        columns = [desc[0] for desc in cursor.description]
        results = [dict(zip(columns, row)) for row in rows]
    return jsonify(results)
@app.route('/data_overview', methods=['POST'])
def add_data_overview():
    new_data = request.json
    with connection.cursor() as cursor:
        cursor.execute("""
            INSERT INTO data_overview (column1, column2, column3) 
            VALUES (:1, :2, :3)
        """, (new_data['column1'], new_data['column2'], new_data['column3']))
        connection.commit()
    return jsonify({"message": "Data added successfully."}), 201
@app.route('/data_overview/<int:data_id>', methods=['PUT'])
def update_data_overview(data_id):
    updated_data = request.json
    with connection.cursor() as cursor:
        cursor.execute("""
            UPDATE data_overview
            SET column1 = :1, column2 = :2, column3 = :3
            WHERE id = :4
        """, (updated_data['column1'], updated_data['column2'], updated_data['column3
'], data_id))
        connection.commit()
    return jsonify({"message": "Data updated successfully."})
@app.route('/data_overview/<int:data_id>', methods=['DELETE'])
def delete_data_overview(data_id):
    with connection.cursor() as cursor:
        cursor.execute("DELETE FROM data_overview WHERE id = :1", (data_id,))
        connection.commit()
    return jsonify({"message": "Data deleted successfully."})
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, render_template, request
import random
import time
import threading
app = Flask(__name__)
data_store = []
clients = []
def generate_random_data():
    while True:
        data_point = {
            'timestamp': time.time(),
            'value': random.uniform(0, 100)
        }
        data_store.append(data_point)
        if len(data_store) > 100:
            data_store.pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/subscribe', methods=['POST'])
def subscribe():
    client_id = request.json.get('client_id')
    clients.append(client_id)
    return jsonify({'status': 'subscribed', 'client_id': client_id})
@app.route('/unsubscribe', methods=['POST'])
def unsubscribe():
    client_id = request.json.get('client_id')
    clients.remove(client_id)
    return jsonify({'status': 'unsubscribed', 'client_id': client_id})
def notify_clients(data):
    for client_id in clients:
        # Here, you would implement the logic to send the data to the client
        pass
data_thread = threading.Thread(target=generate_random_data)
data_thread.daemon = True
data_thread.start()
if __name__ == '__main__':
    app.run(debug=True)
<!doctype html>
<html lang="en">
<head>
    <meta charset="utf-8">
    <title>Real-time Data Visualization</title>
    <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
</head>
<body>
    <h1>Real-time Data Visualization</h1>
    <div id="data-container"></div>
    <script>
        const clientId = Math.random().toString(36).substring(2);
        $(document).ready(function() {
            $.post('/subscribe', JSON.stringify({client_id: clientId}), function(resp
onse) {
                console.log(response);
            });
            setInterval(function() {
                $.get('/data', function(data) {
                    $('#data-container').empty();
                    data.forEach(function(point) {
                        $('#data-container').append('<div>' + point.timestamp + ': ' 
+ point.value + '</div>');
                    });
                });
            }, 1000);
        });
    </script>
</body>
</html>
from flask import Flask, jsonify, request
import random
import threading
import time
import json
from flask_cors import CORS
app = Flask(__name__)
CORS(app)
data_store = []
def generate_random_data():
    while True:
        data_point = {
            'timestamp': time.time(),
            'value': random.uniform(0, 100)
        }
        data_store.append(data_point)
        time.sleep(1)
@app.route('/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/data/clear', methods=['POST'])
def clear_data():
    data_store.clear()
    return jsonify({'status': 'success', 'message': 'data cleared'}), 200
@app.route('/data/latest', methods=['GET'])
def get_latest_data():
    if data_store:
        return jsonify(data_store[-1])
    return jsonify({'error': 'No data available'}), 404
@app.route('/data/range', methods=['GET'])
def get_data_range():
    start_time = request.args.get('start_time', type=float)
    end_time = request.args.get('end_time', type=float)
    filtered_data = [point for point in data_store if start_time <= point['timestamp'
] <= end_time]
    return jsonify(filtered_data)
@app.route('/data/statistics', methods=['GET'])
def get_statistics():
    if not data_store:
        return jsonify({'error': 'No data available'}), 404
    values = [point['value'] for point in data_store]
    average = sum(values) / len(values)
    minimum = min(values)
    maximum = max(values)
    return jsonify({
        'average': average,
        'min': minimum,
        'max': maximum,
        'count': len(values)
    })
if __name__ == '__main__':
    data_generator = threading.Thread(target=generate_random_data)
    data_generator.daemon = True
    data_generator.start()
    app.run(host='0.0.0.0', port=5000)
from flask import Flask, jsonify, request
import cx_Oracle
app = Flask(__name__)
def get_db_connection():
    dsn = cx_Oracle.makedsn('host', 'port', service_name='service_name')
    connection = cx_Oracle.connect(user='username', password='password', dsn=dsn)
    return connection
@app.route('/api/overview', methods=['GET'])
def get_overview():
    data = {
        "data": [
            {
                "data": [
                    {"name": "活跃用户数", "value": 2500},
                    {"name": "注册用户总数", "value": 7500},
                    {"name": "日均访问次数", "value": 15000}
                ],
                "type": "census",
                "count": 3
            },
            {
                "data": {
                    "data": [
                        {"user_id": "U001", "duration": 120, "login_time": "2023-10-0
1 09:30:00", "action_type": "点击", "device_type": "手机", "visited_page": "首页"},
                        {"user_id": "U002", "duration": 300, "login_time": "2023-10-0
1 10:15:00", "action_type": "浏览", "device_type": "电脑", "visited_page": "数据报表"
},
                        {"user_id": "U003", "duration": 75, "login_time": "2023-10-01
 11:00:00", "action_type": "修改", "device_type": "平板", "visited_page": "用户设置"}
,
                        {"user_id": "U004", "duration": 180, "login_time": "2023-10-0
1 11:30:00", "action_type": "查询", "device_type": "手机", "visited_page": "帮助中心"
},
                        {"user_id": "U005", "duration": 240, "login_time": "2023-10-0
1 12:00:00", "action_type": "咨询", "device_type": "电脑", "visited_page": "在线客服"
},
                        {"user_id": "U006", "duration": 60, "login_time": "2023-10-01
 12:30:00", "action_type": "提交", "device_type": "手机", "visited_page": "反馈"},
                        {"user_id": "U007", "duration": 90, "login_time": "2023-10-01
 13:00:00", "action_type": "查看", "device_type": "平板", "visited_page": "个人资料"}
,
                        {"user_id": "U008", "duration": 150, "login_time": "2023-10-0
1 13:30:00", "action_type": "浏览", "device_type": "电脑", "visited_page": "统计分析"
}
                    ],
                    "header": [
                        {"th": "用户ID", "value": "user_id"},
                        {"th": "登录时间", "value": "login_time"},
                        {"th": "访问页面", "value": "visited_page"},
                        {"th": "操作类型", "value": "action_type"},
                        {"th": "持续时间(秒)", "value": "duration"},
                        {"th": "设备类型", "value": "device_type"}
                    ]
                },
                "type": "table",
                "count": 1,
                "tdcount": 8,
                "thcount": 6
            }
        ],
        "name": "用户行为统计",
        "type": "statistics",
        "index": 4
    }
    return jsonify(data)
if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)
from flask import Flask, jsonify, request, abort
import logging
app = Flask(__name__)
# Configure logging
logging.basicConfig(level=logging.ERROR)
class CustomError(Exception):
    status_code = 500
    def __init__(self, message, status_code=None):
        Exception.__init__(self)
        self.message = message
        if status_code is not None:
            self.status_code = status_code
    def to_dict(self):
        return {'error': self.message}
def handle_error(error):
    if isinstance(error, CustomError):
        response = jsonify(error.to_dict())
        response.status_code = error.status_code
    else:
        response = jsonify({'error': 'Internal Server Error'})
        response.status_code = 500
    return response
@app.errorhandler(CustomError)
def custom_error_handler(error):
    return handle_error(error)
@app.errorhandler(Exception)
def general_exception_handler(error):
    logging.error(f"Unhandled Exception: {str(error)}", exc_info=True)
    return handle_error(CustomError("An unexpected error occurred", status_code=500))
@app.route('/data', methods=['GET'])
def get_data():
    try:
        # Simulate a potential error
        if 'id' not in request.args:
            raise CustomError("Missing 'id' parameter", status_code=400)
        data_id = request.args['id']
        if not data_id.isdigit():
            raise CustomError("'id' must be a number", status_code=400)
        # Simulated data retrieval logic
        data = retrieve_data(data_id)
        if data is None:
            raise CustomError("Data not found", status_code=404)
        return jsonify(data), 200
    except CustomError as e:
        return handle_error(e)
    except Exception as e:
        logging.error(f"Error in get_data: {str(e)}", exc_info=True)
        return handle_error(CustomError("An unexpected error occurred", status_code=500))
def retrieve_data(data_id):
    # Simulated database of data
    simulated_database = {"1": "data for id 1", "2": "data for id 2"}
    return simulated_database.get(data_id, None)
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, request
import random
import time
import threading
app = Flask(__name__)
data_store = []
def generate_random_data():
    while True:
        new_data = {
            'timestamp': time.time(),
            'value': random.uniform(0, 100)
        }
        data_store.append(new_data)
        time.sleep(1)
@app.route('/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/data/latest', methods=['GET'])
def get_latest_data():
    if data_store:
        return jsonify(data_store[-1])
    return jsonify({"error": "No data available"}), 404
@app.route('/data/clear', methods=['POST'])
def clear_data():
    data_store.clear()
    return jsonify({"message": "Data cleared successfully"}), 200
@app.route('/data/range', methods=['GET'])
def get_data_range():
    start_time = request.args.get('start', type=float)
    end_time = request.args.get('end', type=float)
    filtered_data = [d for d in data_store if start_time <= d['timestamp'] <= end_time]
    return jsonify(filtered_data)
if __name__ == '__main__':
    threading.Thread(target=generate_random_data, daemon=True).start()
    app.run(debug=True, host='0.0.0.0', port=5000)
from flask import Flask, jsonify, request
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'oracle://username:password@host:port/service
_name'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
class UserBehavior(db.Model):
    __tablename__ = 'user_behavior'
    id = db.Column(db.Integer, primary_key=True)
    user_id = db.Column(db.Integer, nullable=False)
    action = db.Column(db.String(50), nullable=False)
    timestamp = db.Column(db.DateTime, server_default=func.now())
class UserVisitStats(db.Model):
    __tablename__ = 'user_visit_stats'
    id = db.Column(db.Integer, primary_key=True)
    visit_date = db.Column(db.Date, nullable=False)
    user_count = db.Column(db.Integer, nullable=False)
class ClickBehavior(db.Model):
    __tablename__ = 'click_behavior'
    id = db.Column(db.Integer, primary_key=True)
    user_id = db.Column(db.Integer, nullable=False)
    element_clicked = db.Column(db.String(100), nullable=False)
    timestamp = db.Column(db.DateTime, server_default=func.now())
class ConversionRate(db.Model):
    __tablename__ = 'conversion_rate'
    id = db.Column(db.Integer, primary_key=True)
    action_type = db.Column(db.String(50), nullable=False)
    conversion_count = db.Column(db.Integer, nullable=False)
    total_visits = db.Column(db.Integer, nullable=False)
class RetentionRate(db.Model):
    __tablename__ = 'retention_rate'
    id = db.Column(db.Integer, primary_key=True)
    user_id = db.Column(db.Integer, nullable=False)
    retention_period = db.Column(db.Integer, nullable=False)
    active = db.Column(db.Boolean, nullable=False)
@app.route('/api/user_behavior_analysis', methods=['GET'])
def user_behavior_analysis():
    visit_stats = UserVisitStats.query.with_entities(func.sum(UserVisitStats.user_cou
nt)).scalar()
    click_count = ClickBehavior.query.count()
    conversion_data = ConversionRate.query.with_entities(func.sum(ConversionRate.conv
ersion_count), func.sum(ConversionRate.total_visits)).first()
    retention_rate_data = RetentionRate.query.filter_by(active=True).count()
    response_data = {
        "data": [
            {
                "data": [
                    {"name": "用户访问统计", "count": visit_stats},
                    {"name": "点击行为分析", "count": click_count},
                    {"name": "转化率追踪", "conversion_count": conversion_data[0], "t
otal_visits": conversion_data[1]},
                    {"name": "留存率评估", "count": retention_rate_data},
                ],
                "type": "scenesidebar",
                "count": 4
            }
        ],
        "name": "用户行为分析侧边栏",
        "type": "sidebar",
        "index": 1
    }
    return jsonify(response_data)
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, render_template
import random
import numpy as np
import pandas as pd
from threading import Thread
import time
app = Flask(__name__)
data_store = []
def generate_random_data():
    while True:
        new_data_point = {
            'timestamp': pd.Timestamp.now(),
            'value': random.uniform(0, 100)
        }
        data_store.append(new_data_point)
        if len(data_store) > 1000:
            data_store.pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/api/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/api/statistics', methods=['GET'])
def get_statistics():
    df = pd.DataFrame(data_store)
    if df.empty:
        return jsonify({"mean": None, "max": None, "min": None})
    stats = {
        "mean": df['value'].mean(),
        "max": df['value'].max(),
        "min": df['value'].min()
    }
    return jsonify(stats)
if __name__ == '__main__':
    Thread(target=generate_random_data).start()
    app.run(debug=True)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-Time Data Visualization</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>Real-Time Data Visualization</h1>
    <canvas id="dataChart" width="400" height="200"></canvas>
    <div>
        <h2>Statistics</h2>
        <p>Mean: <span id="mean"></span></p>
        <p>Max: <span id="max"></span></p>
        <p>Min: <span id="min"></span></p>
    </div>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        const dataChart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: 'Random Data',
                    data: [],
                    borderColor: 'rgba(75, 192, 192, 1)',
                    fill: false
                }]
            },
            options: {
                scales: {
                    x: {
                        type: 'time'
                    },
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        function fetchData() {
            fetch('/api/data')
                .then(response => response.json())
                .then(data => {
                    dataChart.data.labels = data.map(d => d.timestamp);
                    dataChart.data.datasets[0].data = data.map(d => d.value);
                    dataChart.update();
                });
            fetch('/api/statistics')
                .then(response => response.json())
                .then(stats => {
                    document.getElementById('mean').textContent = stats.mean;
                    document.getElementById('max').textContent = stats.max;
                    document.getElementById('min').textContent = stats.min;
                });
        }
        setInterval(fetchData, 2000);
    </script>
</body>
</html>
from flask import Flask, jsonify, request
import cx_Oracle
app = Flask(__name__)
class DatabaseConnection:
    def __init__(self, user, password, dsn):
        self.user = user
        self.password = password
        self.dsn = dsn
        self.connection = None
        self.cursor = None
    def connect(self):
        if self.connection is None:
            self.connection = cx_Oracle.connect(self.user, self.password, self.dsn)
            self.cursor = self.connection.cursor()
    def close(self):
        if self.cursor:
            self.cursor.close()
        if self.connection:
            self.connection.close()
    def execute_query(self, query, params=None):
        self.connect()
        try:
            self.cursor.execute(query, params)
            return self.cursor.fetchall()
        except Exception as e:
            return str(e)
        finally:
            self.close()
    def execute_non_query(self, query, params=None):
        self.connect()
        try:
            self.cursor.execute(query, params)
            self.connection.commit()
        except Exception as e:
            return str(e)
        finally:
            self.close()
class DataRepository:
    def __init__(self, db_connection):
        self.db_connection = db_connection
    def get_data(self, start_date, end_date):
        query = "SELECT * FROM real_time_data WHERE timestamp BETWEEN :start_date AND
 :end_date"
        return self.db_connection.execute_query(query, {'start_date': start_date, 'en
d_date': end_date})
    def insert_data(self, data):
        query = "INSERT INTO real_time_data (timestamp, value) VALUES (:timestamp, :v
alue)"
        return self.db_connection.execute_non_query(query, {'timestamp': data['timest
amp'], 'value': data['value']})
db_config = {
    'user': 'your_username',
    'password': 'your_password',
    'dsn': 'your_dsn'
}
db_connection = DatabaseConnection(db_config['user'], db_config['password'], db_confi
g['dsn'])
data_repository = DataRepository(db_connection)
@app.route('/data', methods=['GET'])
def fetch_data():
    start_date = request.args.get('start_date')
    end_date = request.args.get('end_date')
    data = data_repository.get_data(start_date, end_date)
    return jsonify(data)
@app.route('/data', methods=['POST'])
def add_data():
    data = request.json
    result = data_repository.insert_data(data)
    if result is None:
        return jsonify({"message": "Data inserted successfully."}), 201
    else:
        return jsonify({"error": result}), 400
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, request
import cx_Oracle
app = Flask(__name__)
def get_db_connection():
    dsn = cx_Oracle.makedsn('HOST', 'PORT', service_name='SERVICE_NAME')
    connection = cx_Oracle.connect(user='USERNAME', password='PASSWORD', dsn=dsn)
    return connection
@app.route('/api/overview', methods=['GET'])
def get_overview_data():
    connection = get_db_connection()
    cursor = connection.cursor()
    cursor.execute("SELECT COUNT(*) FROM users WHERE status = 'registered'")
    registered_users_count = cursor.fetchone()[0]
    cursor.execute("SELECT COUNT(*) FROM users WHERE status = 'active'")
    active_users_count = cursor.fetchone()[0]
    cursor.execute("SELECT COUNT(*) FROM data_requests")
    data_requests_count = cursor.fetchone()[0]
    cursor.execute("SELECT COUNT(*) FROM realtime_monitoring")
    realtime_monitoring_count = cursor.fetchone()[0]
    cursor.execute("SELECT COUNT(*) FROM alerts WHERE status = 'triggered'")
    alerts_count = cursor.fetchone()[0]
    cursor.close()
    connection.close()
    response_data = {
        "data": [
            {
                "data": [
                    {"name": "注册用户数量", "value": registered_users_count},
                    {"name": "活跃用户数量", "value": active_users_count},
                    {"name": "数据请求次数", "value": data_requests_count},
                    {"name": "实时检测数量", "value": realtime_monitoring_count},
                    {"name": "故障报警数量", "value": alerts_count}
                ],
                "type": "census",
                "count": 5
            },
            {
                "data": {
                    "data": [],
                    "header": [
                        {"th": "检测日期", "value": "test_date"},
                        {"th": "样本编号", "value": "sample_id"},
                        {"th": "检测项目", "value": "test_item"},
                        {"th": "仪器编号", "value": "instrument_id"},
                        {"th": "检测结果", "value": "test_result"}
                    ]
                },
                "type": "table",
                "count": 1,
                "tdcount": 0,
                "thcount": 3
            }
        ],
        "name": "关键指标可视化",
        "type": "echart",
        "index": 2
    }
    return jsonify(response_data)
@app.route('/api/realtime_data', methods=['GET'])
def get_realtime_data():
    connection = get_db_connection()
    cursor = connection.cursor()
    cursor.execute("""
        SELECT sample_id, test_date, test_item, test_result, instrument_id, test_pers
onnel, test_report_image, monitoring_location 
        FROM environment_monitoring 
        WHERE ROWNUM <= 8
    """)
    rows = cursor.fetchall()
    cursor.close()
    connection.close()
    data = []
    for row in rows:
        data.append({
            "sample_id": row[0],
            "test_date": row[1],
            "test_item": row[2],
            "test_result": row[3],
            "instrument_id": row[4],
            "test_personnel": row[5],
            "test_report_image": row[6],
            "monitoring_location": row[7]
        })
    response_data = {
        "data": {
            "data": data,
            "header": [
                {"th": "检测日期", "value": "test_date"},
                {"th": "样本编号", "value": "sample_id"},
                {"th": "检测项目", "value": "test_item"},
                {"th": "仪器编号", "value": "instrument_id"},
                {"th": "检测结果", "value": "test_result"}
            ]
        },
        "type": "table",
        "count": 1,
        "tdcount": len(data),
        "thcount": 5
    }
    return jsonify(response_data)
if __name__ == '__main__':
    app.run(debug=True)
import unittest
from flask import Flask, jsonify
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///test.db'
db = SQLAlchemy(app)
class DataModel(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    value = db.Column(db.Float, nullable=False)
@app.route('/data', methods=['POST'])
def add_data():
    new_data = request.json.get('value')
    if new_data is None:
        return jsonify({'error': 'No data provided'}), 400
    data_entry = DataModel(value=new_data)
    db.session.add(data_entry)
    db.session.commit()
    return jsonify({'id': data_entry.id, 'value': data_entry.value}), 201
@app.route('/data/<int:data_id>', methods=['GET'])
def get_data(data_id):
    data_entry = DataModel.query.get(data_id)
    if not data_entry:
        return jsonify({'error': 'Data not found'}), 404
    return jsonify({'id': data_entry.id, 'value': data_entry.value})
@app.route('/data/<int:data_id>', methods=['DELETE'])
def delete_data(data_id):
    data_entry = DataModel.query.get(data_id)
    if not data_entry:
        return jsonify({'error': 'Data not found'}), 404
    db.session.delete(data_entry)
    db.session.commit()
    return jsonify({'message': 'Data deleted successfully'}), 200
class TestDataModel(unittest.TestCase):
    def setUp(self):
        self.app = app.test_client()
        db.create_all()
    def tearDown(self):
        db.session.remove()
        db.drop_all()
    def test_add_data_success(self):
        response = self.app.post('/data', json={'value': 10.5})
        self.assertEqual(response.status_code, 201)
        self.assertIn('id', response.get_json())
        self.assertEqual(response.get_json()['value'], 10.5)
    def test_add_data_missing_value(self):
        response = self.app.post('/data', json={})
        self.assertEqual(response.status_code, 400)
        self.assertEqual(response.get_json()['error'], 'No data provided')
    def test_get_data_success(self):
        self.app.post('/data', json={'value': 15.0})
        response = self.app.get('/data/1')
        self.assertEqual(response.status_code, 200)
        self.assertEqual(response.get_json()['value'], 15.0)
    def test_get_data_not_found(self):
        response = self.app.get('/data/999')
        self.assertEqual(response.status_code, 404)
        self.assertEqual(response.get_json()['error'], 'Data not found')
    def test_delete_data_success(self):
        self.app.post('/data', json={'value': 20.0})
        response = self.app.delete('/data/1')
        self.assertEqual(response.status_code, 200)
        self.assertEqual(response.get_json()['message'], 'Data deleted successfully')
    def test_delete_data_not_found(self):
        response = self.app.delete('/data/999')
        self.assertEqual(response.status_code, 404)
        self.assertEqual(response.get_json()['error'], 'Data not found')
if __name__ == '__main__':
    unittest.main()
from flask import Flask, jsonify, render_template
from flask_socketio import SocketIO
import numpy as np
import random
import time
import threading
app = Flask(__name__)
app.config['SECRET_KEY'] = 'secret!'
socketio = SocketIO(app)
data_points = []
def generate_random_data():
    while True:
        value = random.uniform(0, 100)
        timestamp = time.time()
        data_points.append({'time': timestamp, 'value': value})
        socketio.emit('data_update', {'time': timestamp, 'value': value})
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/data', methods=['GET'])
def get_data():
    return jsonify(data_points[-50:])
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    socketio.run(app, debug=True)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-time Data Visualization</title>
    <script src="https://code.jquery.com/jquery-3.5.1.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/socket.io/4.0.0/socket.io.min
.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>Real-time Data Visualization</h1>
    <canvas id="dataChart" width="400" height="200"></canvas>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        let chartData = {
            labels: [],
            datasets: [{
                label: 'Random Data',
                data: [],
                borderColor: 'rgba(75, 192, 192, 1)',
                borderWidth: 1,
                fill: false
            }]
        };
        const dataChart = new Chart(ctx, {
            type: 'line',
            data: chartData,
            options: {
                scales: {
                    x: {
                        type: 'linear',
                        position: 'bottom'
                    }
                }
            }
        });
        const socket = io();
        socket.on('data_update', function(data) {
            if (chartData.labels.length > 50) {
                chartData.labels.shift();
                chartData.datasets[0].data.shift();
            }
            chartData.labels.push(data.time);
            chartData.datasets[0].data.push(data.value);
            dataChart.update();
        });
    </script>
</body>
</html>
from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import create_engine, Column, Integer, String, DateTime
from sqlalchemy.orm import sessionmaker
from datetime import datetime
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'oracle+cx_oracle://username:password@host:po
rt/dbname'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
class AlertNotification(db.Model):
    __tablename__ = 'alert_notifications'
    id = Column(Integer, primary_key=True)
    message = Column(String(255), nullable=False)
    created_at = Column(DateTime, default=datetime.utcnow)
@app.route('/notifications', methods=['POST'])
def create_notification():
    data = request.json
    new_notification = AlertNotification(message=data['message'])
    db.session.add(new_notification)
    db.session.commit()
    return jsonify({"message": "Notification created", "id": new_notification.id}), 201
@app.route('/notifications', methods=['GET'])
def get_notifications():
    notifications = AlertNotification.query.all()
    output = [{"id": n.id, "message": n.message, "created_at": n.created_at} for n in
 notifications]
    return jsonify(output)
@app.route('/notifications/<int:notification_id>', methods=['GET'])
def get_notification(notification_id):
    notification = AlertNotification.query.get_or_404(notification_id)
    return jsonify({"id": notification.id, "message": notification.message, "created_
at": notification.created_at})
@app.route('/notifications/<int:notification_id>', methods=['PUT'])
def update_notification(notification_id):
    data = request.json
    notification = AlertNotification.query.get_or_404(notification_id)
    notification.message = data['message']
    db.session.commit()
    return jsonify({"message": "Notification updated"})
@app.route('/notifications/<int:notification_id>', methods=['DELETE'])
def delete_notification(notification_id):
    notification = AlertNotification.query.get_or_404(notification_id)
    db.session.delete(notification)
    db.session.commit()
    return jsonify({"message": "Notification deleted"})
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, render_template, request
import random
import time
import threading
app = Flask(__name__)
data_buffer = []
def generate_random_data():
    while True:
        data_point = {
            'timestamp': int(time.time()),
            'value': random.uniform(1, 100)
        }
        data_buffer.append(data_point)
        if len(data_buffer) > 100:
            data_buffer.pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/api/data', methods=['GET'])
def get_data():
    return jsonify(data_buffer)
@app.route('/api/latest', methods=['GET'])
def get_latest_data():
    if data_buffer:
        return jsonify(data_buffer[-1])
    return jsonify({'message': 'No data available'}), 404
@app.route('/api/clear', methods=['POST'])
def clear_data():
    data_buffer.clear()
    return jsonify({'message': 'Data cleared'})
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    app.run(debug=True)
<!doctype html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>实时数据分析可视化</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>实时数据分析可视化</h1>
    <canvas id="myChart" width="400" height="200"></canvas>
    <button id="clearData">清除数据</button>
    <script>
        const ctx = document.getElementById('myChart').getContext('2d');
        const labels = [];
        const dataValues = [];
        const myChart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: labels,
                datasets: [{
                    label: '随机数据',
                    data: dataValues,
                    borderColor: 'rgba(75, 192, 192, 1)',
                    borderWidth: 1
                }]
            },
            options: {
                scales: {
                    x: {
                        type: 'linear',
                        position: 'bottom'
                    }
                }
            }
        });
        function fetchData() {
            fetch('/api/data')
                .then(response => response.json())
                .then(data => {
                    labels.length = 0;
                    dataValues.length = 0;
                    data.forEach(point => {
                        labels.push(point.timestamp);
                        dataValues.push(point.value);
                    });
                    myChart.update();
                });
        }
        document.getElementById('clearData').addEventListener('click', () => {
            fetch('/api/clear', { method: 'POST' })
                .then(() => {
                    labels.length = 0;
                    dataValues.length = 0;
                    myChart.update();
                });
        });
        setInterval(fetchData, 1000);
    </script>
</body>
</html>
from flask import Flask, jsonify, render_template, Response
import random
import time
import threading
import collections
app = Flask(__name__)
data_lock = threading.Lock()
data_queue = collections.deque(maxlen=100)
def generate_random_data():
    while True:
        with data_lock:
            data_point = {
                'timestamp': time.time(),
                'value': random.uniform(0, 100)
            }
            data_queue.append(data_point)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/data')
def get_data():
    with data_lock:
        data_list = list(data_queue)
    return jsonify(data_list)
@app.route('/stream')
def stream():
    def event_stream():
        while True:
            with data_lock:
                if data_queue:
                    data_point = data_queue[-1]
                else:
                    data_point = {'timestamp': time.time(), 'value': 0}
            yield f"data: {data_point}\n\n"
            time.sleep(1)
    return Response(event_stream(), mimetype='text/event-stream')
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    app.run(debug=True, threaded=True)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-Time Data Visualization</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>Real-Time Data Visualization</h1>
    <canvas id="dataChart" width="400" height="200"></canvas>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        const dataPoints = [];
        const chart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: 'Random Data',
                    data: [],
                    borderColor: 'rgba(75, 192, 192, 1)',
                    fill: false,
                }]
            },
            options: {
                scales: {
                    x: {
                        type: 'time',
                        time: {
                            unit: 'second'
                        }
                    },
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        const eventSource = new EventSource('/stream');
        eventSource.onmessage = function(event) {
            const dataPoint = JSON.parse(event.data);
            const timestamp = new Date(dataPoint.timestamp * 1000).toLocaleTimeString();
            if (dataPoints.length >= 100) {
                dataPoints.shift();
                chart.data.labels.shift();
                chart.data.datasets[0].data.shift();
            }
            dataPoints.push(dataPoint.value);
            chart.data.labels.push(timestamp);
            chart.data.datasets[0].data.push(dataPoint.value);
            chart.update();
        };
    </script>
</body>
</html>
from flask import Flask, jsonify, render_template
import random
import time
import threading
app = Flask(__name__)
data_queue = []
def generate_random_data():
    while True:
        random_data = {
            'timestamp': time.time(),
            'value': random.uniform(0, 100)
        }
        data_queue.append(random_data)
        if len(data_queue) > 100:
            data_queue.pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/api/data', methods=['GET'])
def get_data():
    return jsonify(data_queue)
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    app.run(debug=True)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>实时数据分析可视化</title>
    <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>实时数据分析可视化</h1>
    <canvas id="dataChart"></canvas>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        const labels = [];
        const data = [];
        const chart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: labels,
                datasets: [{
                    label: '随机数据',
                    data: data,
                    borderColor: 'rgba(75, 192, 192, 1)',
                    borderWidth: 2,
                    fill: false
                }]
            },
            options: {
                scales: {
                    x: {
                        type: 'time',
                        time: {
                            unit: 'second'
                        }
                    },
                    y: {
                        beginAtZero: true
                    }
                }
            }
        });
        function fetchData() {
            $.getJSON('/api/data', function(response) {
                labels.length = 0;
                data.length = 0;
                response.forEach(function(entry) {
                    labels.push(new Date(entry.timestamp * 1000));
                    data.push(entry.value);
                });
                chart.update();
            });
        }
        setInterval(fetchData, 1000);
    </script>
</body>
</html>
from flask import Flask, jsonify, request
import random
import time
import threading
app = Flask(__name__)
data_store = []
def generate_random_data():
    global data_store
    while True:
        value = random.uniform(0, 100)
        timestamp = time.time()
        data_store.append({'value': value, 'timestamp': timestamp})
        if len(data_store) > 100:
            data_store.pop(0)
        time.sleep(1)
@app.route('/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/data/clear', methods=['DELETE'])
def clear_data():
    global data_store
    data_store = []
    return jsonify({'message': 'Data cleared successfully'}), 200
@app.route('/data/latest', methods=['GET'])
def get_latest_data():
    if data_store:
        return jsonify(data_store[-1])
    return jsonify({'message': 'No data available'}), 404
@app.route('/data/stats', methods=['GET'])
def get_statistics():
    if not data_store:
        return jsonify({'message': 'No data available'}), 404
    values = [entry['value'] for entry in data_store]
    avg_value = sum(values) / len(values)
    min_value = min(values)
    max_value = max(values)
    return jsonify({
        'average': avg_value,
        'min': min_value,
        'max': max_value,
        'count': len(data_store)
    })
@app.route('/data/range', methods=['GET'])
def get_data_range():
    start_time = request.args.get('start', type=float)
    end_time = request.args.get('end', type=float)
    if start_time is None or end_time is None:
        return jsonify({'message': 'Start and end parameters are required'}), 400
    filtered_data = [entry for entry in data_store if start_time <= entry['timestamp'
] <= end_time]
    return jsonify(filtered_data)
if __name__ == '__main__':
    data_generator_thread = threading.Thread(target=generate_random_data)
    data_generator_thread.daemon = True
    data_generator_thread.start()
    app.run(host='0.0.0.0', port=5000)
from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy.exc import IntegrityError
from passlib.hash import pbkdf2_sha256
from functools import wraps
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'oracle://username:password@host:port/dbname'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
class User(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    username = db.Column(db.String(80), unique=True, nullable=False)
    password = db.Column(db.String(200), nullable=False)
    role = db.Column(db.String(50))
class Permission(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    name = db.Column(db.String(50), unique=True, nullable=False)
class UserPermissions(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
    permission_id = db.Column(db.Integer, db.ForeignKey('permission.id'), nullable=False)
db.create_all()
def hash_password(password):
    return pbkdf2_sha256.hash(password)
def verify_password(stored_password, provided_password):
    return pbkdf2_sha256.verify(provided_password, stored_password)
def has_permission(permission_name):
    def decorator(f):
        @wraps(f)
        def decorated_function(*args, **kwargs):
            user_id = request.headers.get('user_id')
            user = User.query.get(user_id)
            if not user:
                return jsonify({'error': 'User not found'}), 404
            permissions = UserPermissions.query.join(Permission).filter(UserPermissio
ns.user_id == user.id, Permission.name == permission_name).all()
            if not permissions:
                return jsonify({'error': 'Permission denied'}), 403
            return f(*args, **kwargs)
        return decorated_function
    return decorator
@app.route('/register', methods=['POST'])
def register():
    username = request.json.get('username')
    password = request.json.get('password')
    role = request.json.get('role')
    hashed_password = hash_password(password)
    new_user = User(username=username, password=hashed_password, role=role)
    try:
        db.session.add(new_user)
        db.session.commit()
        return jsonify({'message': 'User registered successfully!'}), 201
    except IntegrityError:
        db.session.rollback()
        return jsonify({'error': 'Username already exists'}), 400
@app.route('/login', methods=['POST'])
def login():
    username = request.json.get('username')
    password = request.json.get('password')
    user = User.query.filter_by(username=username).first()
    if user and verify_password(user.password, password):
        return jsonify({'message': 'Login successful!', 'user_id': user.id}), 200
    return jsonify({'error': 'Invalid credentials'}), 401
@app.route('/permissions', methods=['GET'])
@has_permission('view_permissions')
def get_permissions():
    permissions = Permission.query.all()
    return jsonify([{'id': perm.id, 'name': perm.name} for perm in permissions]), 200
@app.route('/permissions', methods=['POST'])
@has_permission('create_permission')
def create_permission():
    permission_name = request.json.get('name')
    new_permission = Permission(name=permission_name)
    try:
        db.session.add(new_permission)
        db.session.commit()
        return jsonify({'message': 'Permission created successfully!'}), 201
    except IntegrityError:
        db.session.rollback()
        return jsonify({'error': 'Permission already exists'}), 400
@app.route('/assign_permission', methods=['POST'])
@has_permission('assign_permission')
def assign_permission():
    user_id = request.json.get('user_id')
    permission_id = request.json.get('permission_id')
    user_permission = UserPermissions(user_id=user_id, permission_id=permission_id)
    try:
        db.session.add(user_permission)
        db.session.commit()
        return jsonify({'message': 'Permission assigned successfully!'}), 201
    except IntegrityError:
        db.session.rollback()
        return jsonify({'error': 'Failed to assign permission'}), 400
@app.errorhandler(404)
def not_found(error):
    return jsonify({'error': 'Not found'}), 404
@app.errorhandler(500)
def internal_error(error):
    return jsonify({'error': 'Internal server error'}), 500
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, render_template, jsonify
from flask_socketio import SocketIO
import random
import time
import threading
app = Flask(__name__)
socketio = SocketIO(app)
data_store = []
def generate_random_data():
    while True:
        random_value = random.uniform(0, 100)
        timestamp = time.time()
        data_point = {'timestamp': timestamp, 'value': random_value}
        data_store.append(data_point)
        socketio.emit('new_data', data_point)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/data')
def get_data():
    return jsonify(data_store)
@app.route('/data/clear', methods=['POST'])
def clear_data():
    global data_store
    data_store = []
    return jsonify({'success': True})
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    socketio.run(app, host='0.0.0.0', port=5000)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-time Data Visualization</title>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/socket.io/4.0.0/socket.io.js"
></script>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>Real-time Data Visualization</h1>
    <canvas id="myChart" width="400" height="200"></canvas>
    <button id="clear">Clear Data</button>
    <script>
        const ctx = document.getElementById('myChart').getContext('2d');
        const labels = [];
        const data = {
            labels: labels,
            datasets: [{
                label: 'Random Data',
                backgroundColor: 'rgba(75, 192, 192, 0.2)',
                borderColor: 'rgba(75, 192, 192, 1)',
                borderWidth: 1,
                data: [],
            }]
        };
        const config = {
            type: 'line',
            data: data,
            options: {
                responsive: true,
                scales: {
                    y: {
                        beginAtZero: true
                    }
                }
            }
        };
        const myChart = new Chart(ctx, config);
        const socket = io();
        socket.on('new_data', function(dataPoint){
            const time = new Date(dataPoint.timestamp * 1000).toLocaleTimeString();
            labels.push(time);
            data.datasets[0].data.push(dataPoint.value);
            myChart.update();
        });
        document.getElementById('clear').addEventListener('click', function() {
            fetch('/data/clear', {
                method: 'POST'
            }).then(() => {
                labels.length = 0;
                data.datasets[0].data.length = 0;
                myChart.update();
            });
        });
    </script>
</body>
</html>
from flask import Flask, jsonify
from functools import wraps
import time
import redis
app = Flask(__name__)
cache = redis.StrictRedis(host='localhost', port=6379, db=0)
def cache_key(func_name, *args, **kwargs):
    return f"{func_name}:{args}:{kwargs}"
def cache_result(timeout=60):
    def decorator(func):
        @wraps(func)
        def wrapped(*args, **kwargs):
            cache_id = cache_key(func.__name__, *args, **kwargs)
            cached_result = cache.get(cache_id)
            if cached_result is not None:
                return jsonify({"data": cached_result.decode('utf-8'), "source": "cache"})
            try:
                result = func(*args, **kwargs)
                cache.setex(cache_id, timeout, result)
                return jsonify({"data": result, "source": "computed"})
            except Exception as e:
                return handle_cache_error(e)
        return wrapped
    return decorator
def handle_cache_error(e):
    error_message = f"Error during caching operation: {str(e)}"
    return jsonify({"error": error_message, "status": 500})
@app.route('/data/<int:item_id>', methods=['GET'])
@cache_result(timeout=120)
def get_data(item_id):
    simulated_data = {"item_id": item_id, "value": f"data for item {item_id}"}
    time.sleep(2)  
    return simulated_data
if __name__ == '__main__':
    app.run(debug=True)
from flask import Flask, jsonify, render_template
import random
import time
import threading
app = Flask(__name__)
data_store = {
    'temperature': [],
    'humidity': [],
    'timestamp': []
}
def generate_random_data():
    while True:
        temperature = round(random.uniform(20.0, 30.0), 2)
        humidity = round(random.uniform(30.0, 70.0), 2)
        current_time = time.strftime("%Y-%m-%d %H:%M:%S")
        data_store['temperature'].append(temperature)
        data_store['humidity'].append(humidity)
        data_store['timestamp'].append(current_time)
        if len(data_store['temperature']) > 100:
            data_store['temperature'].pop(0)
            data_store['humidity'].pop(0)
            data_store['timestamp'].pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/data')
def get_data():
    return jsonify(data_store)
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    app.run(host='0.0.0.0', port=5000)
<!-- templates/index.html -->
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>实时数据分析可视化</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
    <style>
        body { font-family: Arial, sans-serif; }
        canvas { max-width: 800px; margin: 0 auto; }
    </style>
</head>
<body>
    <h1>实时温度和湿度图表</h1>
    <canvas id="dataChart"></canvas>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        let dataChart;
        fetch('/data')
            .then(response => response.json())
            .then(data => {
                dataChart = new Chart(ctx, {
                    type: 'line',
                    data: {
                        labels: data.timestamp,
                        datasets: [
                            {
                                label: '温度 (°C)',
                                data: data.temperature,
                                borderColor: 'rgba(255, 99, 132, 1)',
                                borderWidth: 2,
                                fill: false
                            },
                            {
                                label: '湿度 (%)',
                                data: data.humidity,
                                borderColor: 'rgba(54, 162, 235, 1)',
                                borderWidth: 2,
                                fill: false
                            }
                        ]
                    },
                    options: {
                        scales: {
                            x: {
                                type: 'time',
                                time: {
                                    unit: 'second'
                                },
                                title: {
                                    display: true,
                                    text: '时间'
                                }
                            },
                            y: {
                                title: {
                                    display: true,
                                    text: '值'
                                }
                            }
                        }
                    }
                });
                setInterval(() => {
                    fetch('/data')
                        .then(response => response.json())
                        .then(newData => {
                            if (dataChart.data.labels.length > 100) {
                                dataChart.data.labels.shift();
                                dataChart.data.datasets[0].data.shift();
                                dataChart.data.datasets[1].data.shift();
                            }
                            dataChart.data.labels.push(newData.timestamp[newData.time
stamp.length - 1]);
                            dataChart.data.datasets[0].data.push(newData.temperature[
newData.temperature.length - 1]);
                            dataChart.data.datasets[1].data.push(newData.humidity[new
Data.humidity.length - 1]);
                            dataChart.update();
                        });
                }, 1000);
            });
    </script>
</body>
</html>
from flask import Flask, jsonify, request
import logging
from werkzeug.exceptions import HTTPException
app = Flask(__name__)
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class MiddlewareException(Exception):
    pass
def log_request_data():
    logger.info("Request data: %s", request.get_json())
def middleware_error_handling(error):
    if isinstance(error, MiddlewareException):
        response = jsonify({"message": str(error), "status": "error"})
        response.status_code = 400
        return response
    elif isinstance(error, HTTPException):
        response = jsonify({"message": error.description, "status": "error"})
        response.status_code = error.code
        return response
    else:
        response = jsonify({"message": "Internal server error", "status": "error"})
        response.status_code = 500
        return response
@app.before_request
def before_request():
    log_request_data()
@app.errorhandler(Exception)
def handle_exception(error):
    return middleware_error_handling(error)
def validate_data(data):
    if not data or 'key' not in data:
        raise MiddlewareException("Invalid data: 'key' is required.")
@app.route('/data', methods=['POST'])
def process_data():
    data = request.get_json()
    try:
        validate_data(data)
        # Simulate processing data
        processed_data = {"key": data['key'], "status": "processed"}
        logger.info("Processed data: %s", processed_data)
        return jsonify(processed_data), 200
    except MiddlewareException as e:
        return middleware_error_handling(e)
if __name__ == "__main__":
    app.run(debug=True)
from flask import Flask, jsonify, render_template
import random
import time
import threading
import json
app = Flask(__name__)
data_store = []
def generate_random_data():
    while True:
        timestamp = time.strftime('%Y-%m-%d %H:%M:%S')
        value = random.uniform(0, 100)
        data_store.append({'timestamp': timestamp, 'value': value})
        if len(data_store) > 100:
            data_store.pop(0)
        time.sleep(1)
@app.route('/')
def index():
    return render_template('index.html')
@app.route('/api/data')
def get_data():
    return jsonify(data_store)
if __name__ == '__main__':
    threading.Thread(target=generate_random_data, daemon=True).start()
    app.run(debug=True)
<!doctype html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Real-time Data Visualization</title>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/2.9.4/Chart.min.js">
</script>
</head>
<body>
    <canvas id="dataChart" width="400" height="200"></canvas>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        let chart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: 'Random Data',
                    data: [],
                    borderColor: 'rgba(75, 192, 192, 1)',
                    fill: false
                }]
            },
            options: {
                scales: {
                    xAxes: [{
                        type: 'time',
                        time: {
                            unit: 'second'
                        }
                    }],
                    yAxes: [{
                        ticks: {
                            beginAtZero: true
                        }
                    }]
                }
            }
        });
        function fetchData() {
            fetch('/api/data')
                .then(response => response.json())
                .then(data => {
                    chart.data.labels = data.map(entry => entry.timestamp);
                    chart.data.datasets[0].data = data.map(entry => entry.value);
                    chart.update();
                });
        }
        setInterval(fetchData, 1000);
    </script>
</body>
</html>
from flask import Flask, jsonify, render_template
import random
import time
import threading
app = Flask(__name__)
data_store = []
def generate_random_data():
    while True:
        new_data = {
            'timestamp': time.time(),
            'value': random.uniform(0, 100)
        }
        data_store.append(new_data)

from flask import Flask, jsonify, render_template
import random
import time
import threading
app = Flask(__name__)
data_store = []
def generate_random_data():
    while True:
        data_point = {
            'timestamp': time.time(),
            'value': random.uniform(0, 100)
        }
        data_store.append(data_point)
        time.sleep(1)
@app.route('/api/data', methods=['GET'])
def get_data():
    return jsonify(data_store)
@app.route('/')
def index():
    return render_template('index.html')
if __name__ == '__main__':
    data_thread = threading.Thread(target=generate_random_data)
    data_thread.daemon = True
    data_thread.start()
    app.run(debug=True, host='0.0.0.0', port=5000)
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>实时数据分析可视化系统</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
    <h1>实时数据分析可视化</h1>
    <canvas id="dataChart" width="400" height="200"></canvas>
    <script>
        const ctx = document.getElementById('dataChart').getContext('2d');
        let chart = new Chart(ctx, {
            type: 'line',
            data: {
                labels: [],
                datasets: [{
                    label: '随机数据',
                    data: [],
                    borderColor: 'rgba(75, 192, 192, 1)',
                    fill: false
                }]
            },
            options: {
                scales: {
                    x: {
                        type: 'linear',
                        position: 'bottom'
                    }
                }
            }
        });
        async function fetchData() {
            const response = await fetch('/api/data');
            const data = await response.json();
            chart.data.labels = data.map(point => point.timestamp);
            chart.data.datasets[0].data = data.map(point => point.value);
            chart.update();
        }
        setInterval(fetchData, 2000);
    </script>
</body>
</html>
from flask import Flask, request
import logging
import os
from logging.handlers import RotatingFileHandler
app = Flask(__name__)
log_dir = 'logs'
if not os.path.exists(log_dir):
    os.makedirs(log_dir)
log_file = os.path.join(log_dir, 'app.log')
logger = logging.getLogger('MyLogger')
logger.setLevel(logging.DEBUG)
handler = RotatingFileHandler(log_file, maxBytes=10*1024*1024, backupCount=5)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
logger.addHandler(handler)
def log_error(message):
    logger.error(message)
def log_info(message):
    logger.info(message)
def log_warning(message):
    logger.warning(message)
def log_debug(message):
    logger.debug(message)
@app.route('/data', methods=['POST'])
def data_endpoint():
    try:
        data = request.json
        if not data:
            log_error('No data received')
            return {'error': 'No data received'}, 400
        process_data(data)
        log_info('Data processed successfully')
        return {'status': 'success'}, 200
    except Exception as e:
        log_error(f'Error processing data: {str(e)}')
        return {'error': 'Internal server error'}, 500
def process_data(data):
    if 'value' not in data:
        log_warning('Value not provided in data')
        raise ValueError('Missing value in data')
    # Simulate data processing
    log_debug(f'Processing value: {data["value"]}')
    if data['value'] < 0:
        log_error('Negative value encountered')
        raise ValueError('Value cannot be negative')
    # Further processing...
    log_info('Data processing completed')
if __name__ == '__main__':
    app.run(debug=True)
from flask import jsonify
import pandas as pd
import numpy as np
from datetime import datetime
import logging
import os
class DataUtils:
    @staticmethod
    def load_data(file_path):
        if os.path.exists(file_path):
            return pd.read_csv(file_path)
        else:
            logging.error(f"File not found: {file_path}")
            return None
    @staticmethod
    def filter_data(dataframe, column, value):
        return dataframe[dataframe[column] == value]
    @staticmethod
    def aggregate_data(dataframe, group_by_column, agg_column, agg_func='sum'):
        return dataframe.groupby(group_by_column)[agg_column].agg(agg_func).reset_index()
    @staticmethod
    def format_datetime(date_str, format="%Y-%m-%d %H:%M:%S"):
        return datetime.strptime(date_str, format)
    @staticmethod
    def compute_statistics(dataframe, column):
        stats = {
            'mean': dataframe[column].mean(),
            'median': dataframe[column].median(),
            'std_dev': dataframe[column].std(),
            'min': dataframe[column].min(),
            'max': dataframe[column].max()
        }
        return stats
class JSONResponse:
    @staticmethod
    def success(data, message="Operation successful"):
        return jsonify({"status": "success", "message": message, "data": data})
    @staticmethod
    def error(message="Operation failed", code=400):
        return jsonify({"status": "error", "message": message}), code
class Logger:
    @staticmethod
    def setup_logger(log_file='app.log'):
        logging.basicConfig(filename=log_file, level=logging.INFO,
                            format='%(asctime)s:%(levelname)s:%(message)s')
    @staticmethod
    def log_info(message):
        logging.info(message)
    @staticmethod
    def log_error(message):
        logging.error(message)
class TimeSeriesUtils:
    @staticmethod
    def resample_time_series(dataframe, frequency='D'):
        dataframe['timestamp'] = pd.to_datetime(dataframe['timestamp'])
        dataframe.set_index('timestamp', inplace=True)
        return dataframe.resample(frequency).mean().reset_index()
    @staticmethod
    def create_time_series(start_date, end_date, frequency='D'):
        return pd.date_range(start=start_date, end=end_date, freq=frequency)
    @staticmethod
    def time_series_to_dataframe(time_series, value_column):
        return pd.DataFrame({ 'timestamp': time_series, value_column: np.random.rand(
len(time_series)) })
class NotificationUtils:
    @staticmethod
    def send_email(recipient, subject, body):
        # This is a placeholder for email sending logic
        logging.info(f"Email sent to {recipient} with subject: {subject}")
    @staticmethod
    def send_slack_message(channel, message):
        # This is a placeholder for Slack messaging logic
        logging.info(f"Message sent to {channel}: {message}")
class DataFrameUtils:
    @staticmethod
    def merge_dataframes(df1, df2, on_column, how='inner'):
        return pd.merge(df1, df2, on=on_column, how=how)
    @staticmethod
    def drop_na(dataframe):
        return dataframe.dropna()
    @staticmethod
    def fill_na(dataframe, value):
        return dataframe.fillna(value)
    @staticmethod
    def sort_dataframe(dataframe, column, ascending=True):
        return dataframe.sort_values(by=column, ascending=ascending)
class ChartUtils:
    @staticmethod
    def plot_line_chart(dataframe, x_column, y_column):
        import matplotlib.pyplot as plt
        plt.figure(figsize=(10, 5))
        plt.plot(dataframe[x_column], dataframe[y_column])
        plt.title('Line Chart')
        plt.xlabel(x_column)
        plt.ylabel(y_column)
        plt.grid()
        plt.show()
    @staticmethod
    def plot_bar_chart(dataframe, x_column, y_column):
        import matplotlib.pyplot as plt
        plt.figure(figsize=(10, 5))
        plt.bar(dataframe[x_column], dataframe[y_column])
        plt.title('Bar Chart')
        plt.xlabel(x_column)
        plt.ylabel(y_column)
        plt.grid()
        plt.show()
class Config:
    DEBUG = True
    DATABASE_URI = 'sqlite:///app.db'
    SECRET_KEY = 'your_secret_key_here'
from flask import Flask, jsonify, request
import pandas as pd
import numpy as np
from datetime import datetime
import json
app = Flask(__name__)
class DataProcessor:
    @staticmethod
    def clean_data(df):
        df = df.dropna() 
        df = df[df.applymap(lambda x: isinstance(x, (int, float)) or pd.isnull(x))]
        return df
    @staticmethod
    def normalize_data(df):
        return (df - df.min()) / (df.max() - df.min())
    @staticmethod
    def aggregate_data(df, group_by_columns, agg_functions):
        return df.groupby(group_by_columns).agg(agg_functions).reset_index()
    @staticmethod
    def filter_data(df, filters):
        for column, (condition, value) in filters.items():
            if condition == '==':
                df = df[df[column] == value]
            elif condition == '!=':
                df = df[df[column] != value]
            elif condition == '>':
                df = df[df[column] > value]
            elif condition == '<':
                df = df[df[column] < value]
            elif condition == '>=':
                df = df[df[column] >= value]
            elif condition == '<=':
                df = df[df[column] <= value]
        return df
    @staticmethod
    def time_series_analysis(df, time_column, value_column):
        df[time_column] = pd.to_datetime(df[time_column])
        time_series = df.groupby(df[time_column].dt.date)[value_column].sum().reset_i
ndex()
        return time_series
    @staticmethod
    def compute_statistics(df, column):
        mean = df[column].mean()
        median = df[column].median()
        stddev = df[column].std()
        return {'mean': mean, 'median': median, 'stddev': stddev}
class DataService:
    def __init__(self):
        self.data = pd.DataFrame()
    def load_data(self, file_path):
        self.data = pd.read_csv(file_path)
    def get_data_summary(self):
        return self.data.describe()
    def get_cleaned_data(self):
        return DataProcessor.clean_data(self.data)
    def get_normalized_data(self):
        return DataProcessor.normalize_data(self.data)
    def get_aggregated_data(self, group_by_columns, agg_functions):
        return DataProcessor.aggregate_data(self.data, group_by_columns, agg_functions)
    def get_filtered_data(self, filters):
        return DataProcessor.filter_data(self.data, filters)
    def get_time_series_data(self, time_column, value_column):
        return DataProcessor.time_series_analysis(self.data, time_column, value_column)
    def get_statistics(self, column):
        return DataProcessor.compute_statistics(self.data, column)
@app.route('/load_data', methods=['POST'])
def load_data():
    file_path = request.json.get('file_path')
    service = DataService()
    service.load_data(file_path)
    return jsonify({"message": "Data loaded successfully!"})
@app.route('/data_summary', methods=['GET'])
def data_summary():
    service = DataService()
    summary = service.get_data_summary()
    return jsonify(summary.to_dict())
@app.route('/cleaned_data', methods=['GET'])
def cleaned_data():
    service = DataService()
    cleaned = service.get_cleaned_data()
    return jsonify(cleaned.to_dict(orient='records'))
@app.route('/filtered_data', methods=['POST'])
def filtered_data():
    filters = request.json.get('filters', {})
    service = DataService()
    filtered = service.get_filtered_data(filters)
    return jsonify(filtered.to_dict(orient='records'))
@app.route('/aggregated_data', methods=['POST'])
def aggregated_data():
    group_by_columns = request.json.get('group_by', [])
    agg_functions = request.json.get('agg_functions', {})
    service = DataService()
    aggregated = service.get_aggregated_data(group_by_columns, agg_functions)
    return jsonify(aggregated.to_dict(orient='records'))
@app.route('/time_series', methods=['POST'])
def time_series():
    time_column = request.json.get('time_column')
    value_column = request.json.get('value_column')
    service = DataService()
    time_series_data = service.get_time_series_data(time_column, value_column)
    return jsonify(time_series_data.to_dict(orient='records'))
@app.route('/statistics', methods=['POST'])
def statistics():
    column = request.json.get('column')
    service = DataService()
    stats = service.get_statistics(column)
    return jsonify(stats)
if __name__ == '__main__':
    app.run(debug=True)